Goodness-of-Fit Tests for Bivariate Time Series of Counts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10435342" target="_blank" >RIV/00216208:11320/21:10435342 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ac6.4efOgj" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ac6.4efOgj</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/econometrics9010010" target="_blank" >10.3390/econometrics9010010</a>
Alternative languages
Result language
angličtina
Original language name
Goodness-of-Fit Tests for Bivariate Time Series of Counts
Original language description
This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being entirely nonparametric and the second one being semiparametric computed under the corresponding null hypothesis. The asymptotic distribution of the proposed tests statistics both under the null hypotheses as well as under alternatives is derived and consistency is proved. The case of testing bivariate generalized Poisson autoregression and extension of the methods to dimension higher than two are also discussed. The finite-sample performance of a parametric bootstrap version of the tests is illustrated via a series of Monte Carlo experiments. The article concludes with applications on real data sets and discussion.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA18-08888S" target="_blank" >GA18-08888S: Two-sample change-point</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Econometrics [online]
ISSN
2225-1146
e-ISSN
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Volume of the periodical
9
Issue of the periodical within the volume
1
Country of publishing house
CH - SWITZERLAND
Number of pages
20
Pages from-to
10
UT code for WoS article
000635244300001
EID of the result in the Scopus database
2-s2.0-85102820234